Social media platforms and social enterprise: Bibliometric analysis and systematic review

2023 | International Journal of Information Management | Citations: 0

Authors: Ali, Imran; Balta, Maria; Papadopoulos, Thanos

Abstract: A considerable number of contributions at the intersection of social media platf ... Expand

Abstract: A considerable number of contributions at the intersection of social media platforms and social entrepreneurship has been witnessed over the past decade. The multi-disciplinary nature of current literature necessitates inte­ grative insights on the topic. We thus undertake a two-pronged approach – bibliometric analysis followed by systematic review – to map the extant literature in a structured, objective, and quantitative way. We contribute to the literature as we (i) offer a classification of the literature in three clusters, namely ‘social media platforms, social collaboration and social marketing’, ‘social media platforms and crowdfunding, and ‘social media plat­ forms and crowdsourcing’; (ii) analyze recent research development in each cluster, methodological develop­ ment, countries co-authorship and evolution of research in the area; and (iii) propose a conceptual framework -accompanied by research propositions- that provides an overview of the literature at the intersection of social media platforms, various social entrepreneurial practices and their influence on the social enterprise perfor­ mance. Our review culminates with numerous impactful research avenues for scholarly progression in the area. From a practical standpoint, this review integrates scattered findings into one body, allowing the practitioners and policymakers to discern the role of social media platforms in dealing with emerging societal problems and increasing operational efficiencies of social enterprises (SEs). To the best of our knowledge, this is the first review of its kind, offering unique perspectives at the nexus of social media platforms and SE’s performance. Collapse

Topics: social media crowdsourcing marketing management crowdfunding digital platform

Methods: literature sample bibliometric analysis literature study structured literature research co-citation analysis

Theories: structuration theory dynamic capabilities theory

Creative Appeals in Firm-Generated Content and Product Performance

2022 | Information Systems Research | Citations: 0

Authors: Mu, Jifeng; Zhang, Jonathan; Borah, Abhishek; Qi, Jiayin

Abstract: The authors of this research investigate the effects of hedonic and utilitarian ... Expand

Abstract: The authors of this research investigate the effects of hedonic and utilitarian message appeals in firm-generated content on product performance measured by daily sales. The results from a multiproduct category, large-scale empirical study with data collected from a variety of sources show that hedonic appeals have a higher positive impact than utilitarian appeals on product performance. The authors also illustrate that message appeals have positive effects on product performance only when message quality and message goal consistency surpass a certain threshold and that these positive effects are stronger for hedonic than for utilitarian appeals. The authors further demonstrate that message complexity negatively moderates the effects of hedonic and utilitarian appeals on product performance with a stronger negative moderating effect for hedonic appeals. The research provides guidance on the proper combination of message styles and suggests that firms’ creative capabilities to curate online messages that resonate with consumers can produce significant performance advantages. Collapse

Topics: Twitter Facebook social media personality marketing management

Methods: Student's t-test parametric test instrumental variables estimation sentiment analysis descriptive statistic

The Influence of Design Updates on Users: the Case of Snapchat

2019 | HICSS | Citations: 0

Authors: Franzmann, Daniel; Fischer, Lukas; Holten, Roland

Abstract: Today’s smartphone apps are regularly updated and enhanced through software upda ... Expand

Abstract: Today’s smartphone apps are regularly updated and enhanced through software updates. The case at hand is the popular social multimedia messaging app Snapchat that released a design overhaul in February 2018. While the update neither changed any features nor caused any relevant bugs or crashes, it led to an uproar of Snapchat’s users and significantly decreased its app store ratings and consequently revenue. As a result, Snap Inc., the company behind Snapchat, was forced to reverse design changes to appease their users. The initial adverse effects of the update were surprising; however, after using difference-in-difference tests in combination with sentiment analysis, our results indicate that design updates can be perceived negatively by users. We contribute to IS literature by evaluating the effect of design changes and the role of perceived ease of use in the post-adoption stage. Collapse

Topics: Snapchat mobile application market mobile application digital distribution perceived ease of use

Methods: natural language processing sentiment analysis parametric test longitudinal research Student's t-test

Using big data analytics to study brand authenticity sentiments: The case of Starbucks on Twitter

2019 | International Journal of Information Management | Citations: 1

Authors: Shirdastian, Hamid; Laroche, Michel; Richard, Marie-Odile

Abstract: There is a strong interest among academics and practitioners in studying brandin ... Expand

Abstract: There is a strong interest among academics and practitioners in studying branding issues in the big data era. In this article, we examine the sentiments toward a brand, via brand authenticity, to identify the reasons for positive or negative sentiments on social media. Moreover, in order to increase precision, we investigate sentiment polarity on a five-point scale. From a database containing 2,282,912 English tweets with the keyword ‘Starbucks’, we use a set of 2204 coded tweets both for analyzing brand authenticity and sentiment polarity. First, we examine the tweets qualitatively to gain insights about brand authenticity sentiments. Then we analyze the data quantitatively to establish a framework in which we predict both the brand authenticity dimensions and their sentiment polarity. Through three qualitative studies, we discuss several tweets from the dataset that can be classified under the quality commitment, heritage, uniqueness, and symbolism categories. Using latent semantic analysis (LSA), we extract the common words in each category. We verify the robustness of previous findings with an in-lab experiment. Results from the support vector machine (SVM), as the quantitative research method, illustrate the effectiveness of the proposed procedure of brand authenticity sentiment analysis. It shows high accuracy for both the brand authenticity dimensions’ predictions and their sentiment polarity. We then discuss the theoretical and managerial implications of the studies. Collapse

Topics: Twitter social media database system decision support system information management

Methods: support vector machine sentiment analysis computational algorithm machine learning latent semantic analysis

Theories: marketing theory